Table 1.

Overall model results, model comparison, and fitted parametric values.

	Model Comparison				Model parameters
	Log-likelihood	AIC	BIC	# of param	α	β
Learned val ini	−121.35 ± 32.05	246.70 ± 64.10	253.79 ± 64.10	2	0.25 ± 0.25	4.47 ± 5.19
Zero ini	−125.38 ± 32.79	254.77 ± 65.58	261.86 ± 65.58	2	0.22 ± 0.25	4.30 ± 2.83
Naïve + Softmax	−119.42 ± 30.30	266.85 ± 60.59	316.43 ± 60.59	14	0.22 ± 0.28	10.26 ± 19.25
Naïve + HMM	−123.30 ± 31.38	274.59 ± 62.77	324.17 ± 62.77	14	0.21 ± 0.26	14.69 ± 38.55

Table of overall models, model comparison and fitted parametric values. Learned val ini: Value transfer learning model initialised with learned value. Zero ini: Value transfer learning model initialised with zero. Naïve + Softmax: Probabilistic policy exploration model with softmax function-based policy search. Naïve + HMM: Probabilistic policy exploration model with HMM based policy search. Log-likelihood value: Larger values indicate a better fit. AIC and BIC: Smaller values indicate a better fit. All values are represented as mean ± SD, except number of parameters. HMM: hidden Markov model; AIC: Akaike information criterion; BIC: Bayesian information criterion.